Image focus editing is an interesting research topic and has received a lot of attention recently. Two problems are mainly involved in this topic. One is image refocus, whose interest is to recover a sharpness of a blurry defocused image. The other is defocus magnification. In some photography such as portrait, a shallow depth of field (DOF) is preferred to highlight a foreground subject with a defocused blurry background. But due to limitations of lens and sensors, some cameras (e.g. a point-and-shoot camera) are unable to produce enough defocus effects.
Recently, a number of focus editing algorithms have been proposed, which can be grouped into two types. One is a computational photography, where some additional optical elements or devices are added in the conventional photography to help the sensor code more information about the target scene. The other type is addressed based on image processing technology without changing the camera. Multi-image based method has been widely studied in the past years. However, the more challenging single image based work is presented recently. Bae and Durand proposed a focus map estimation method in “Defocus Magnification” (Eurographics, 2007), in which the defocus magnification is handled with the aid of lens blur in Photoshop®. One bottle neck of this work is the blur estimation part using an unstable brute-force fitting strategy. In addition, a method is proposed by Bando and Nishita in “Towards Digital Refocusing from a Single Photograph” (Pacific Graphics, pp. 363-372, 2007), which requires lots of user interaction to determine the blur kernel from a number of predefined candidates.